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Average Ratings 0 Ratings
Description
Data is essential across various departments in a business, including sales, marketing, and finance. To maximize the effectiveness of this data, it is crucial to ensure its upkeep, security, and oversight throughout its lifecycle. At Uniserv, data quality is a fundamental aspect of our company ethos and the solutions we provide. Our tailored offerings transform your customer master data into a pivotal asset for your organization. The Data Quality Service Hub guarantees superior customer data quality at every location within your enterprise, extending even to international operations. We provide services to correct your address information in line with global standards, utilizing top-tier reference data. Additionally, we verify email addresses, phone numbers, and banking details across various levels of scrutiny. Should your data contain duplicate entries, we can efficiently identify them based on your specified business criteria. The duplicates detected can often be merged automatically following established guidelines or organized for manual review, ensuring a streamlined data management process that enhances operational efficiency. This comprehensive approach to data quality not only supports compliance but also fosters trust and reliability in your customer interactions.
Description
NetOwl NameMatcher, recognized for its excellence in the MITRE Multicultural Name Matching Challenge, delivers unparalleled accuracy, speed, and scalability in name matching solutions. By employing an innovative machine learning framework, NetOwl effectively tackles the intricate challenges of fuzzy name matching. Conventional methods like Soundex, edit distance, and rule-based systems often face significant issues with precision, leading to false positives, and recall, resulting in false negatives, when confronting the diverse fuzzy name matching scenarios outlined previously. In contrast, NetOwl leverages a data-driven, machine learning-based probabilistic strategy to address these name matching difficulties. It automatically generates sophisticated, probabilistic name matching rules from extensive, real-world multi-ethnic name variant datasets. Furthermore, NetOwl employs distinct matching models tailored to various entity types, such as individuals, organizations, and locations. To add to its capabilities, NetOwl also integrates automatic detection of name ethnicity, enhancing its adaptability to the complexities of multicultural name matching. This comprehensive approach ensures a higher level of accuracy and reliability in diverse applications.
API Access
Has API
API Access
Has API
Integrations
ArcGIS
Elasticsearch
Google Maps
IBM Cloud
Kibana
MarkLogic
Palantir Apollo
SAP Store
SolrCommerce
Tableau
Integrations
ArcGIS
Elasticsearch
Google Maps
IBM Cloud
Kibana
MarkLogic
Palantir Apollo
SAP Store
SolrCommerce
Tableau
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Uniserv
Founded
1969
Country
Germany
Website
www.uniserv.com/en/business-cases/customer-data-management/data-quality/
Vendor Details
Company Name
NetOwl
Founded
1996
Country
United States
Website
www.netowl.com/name-matching-software
Product Features
Data Quality
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management
Product Features
Data Quality
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management